Data as of Sep 17, 2026 · Based on 3,310,041 AI responses across 10,525 prompts · See how Parse measures this
OpenRLHFopenrlhf.readthedocs.ioOpenRLHF is an open-source, production-ready framework for reinforcement learning from human feedback (RLHF). It combines a Ray + vLLM distributed architecture with a unified agent-based execution paradigm to enable scalable, extensible RLHF for very large models (70B+ parameters) and supports both single-turn and multi-turn interactions. It provides state-of-the-art RL algorithms (PPO, REINFORCE variants, GRPO, etc.), vision-language RLHF, async training with partial rollout, and production-grade features such as resumable checkpoints, logging, and multi-node deployment.
The market map · 5 of 89 labelled
RLHF Data Collection & Training Platforms →72%positive
Where OpenRLHF ranks in AI
high-performanceopen-sourcescalablelarge-scalehighly scalableidealflexibleleading
Hugging Face TRLco-mentionedCompare →
Argillaco-mentionedCompare →Excerpts where OpenRLHF appeared in the AI's answer
OpenRLHF : An open-source, high-performance framework built on Ray, vLLM, and DeepSpeed.
OpenRLHF: A highly scalable, easy-to-use open-source framework built on Ray, vLLM, and DeepSpeed.
Excerpts where OpenRLHF appeared in the AI's answer
OpenRLHF: Currently one of the most scalable, production-ready open-source frameworks.
OpenRLHF: A high-performance, open-source distributed training framework
Excerpts where OpenRLHF appeared in the AI's answer
OpenRLHF: A high-performance, lightweight distributed framework built on Ray and DeepSpeed.
OpenRLHF: Built on Ray, OpenRLHF uses a distributed actor-pool design that shines for larger models and heterogeneous GPU clusters
Excerpts where OpenRLHF appeared in the AI's answer
OpenRLHF: A high-performance, scalable open-source framework supporting PPO, DPO, and reward-model training using Ray and DeepSpeed.
OpenRLHF / VeRL : Essential if your "reinforcement learning" targets Large Language Models (LLMs)
Excerpts where OpenRLHF appeared in the AI's answer
OpenRLHF : Built on Ray and DeepSpeed for large-scale, high-performance distributed preference modeling and training.
